Data Analyst (Payrisk)

Get to know our Team:

• Manage the processes and team responsible for accurate data collection, processing, modeling and analysis.

• The ideal candidate has a knack for seeing solutions in sprawling data sets and the business mindset to convert insights into strategic opportunities for our company.

Get to know the Role:

• Work closely with leaders across PayOps, Payment Risk , Chargeback, Training, Products, and other department to support and implement high-quality, data-driven decisions. Ensure data accuracy and consistent reporting by designing and creating optimal processes and procedures for analytics employees to follow.

• Use advanced data modeling and analytical techniques to interpret key findings from data and leverage these insights into initiatives that will support business outcomes.

• Apply their exhaustive knowledge of data analysis to solving real-world problems faced by PayRisk and finding opportunities for improvement across multiple projects, teams and business units.

The day-to-day activities:

• Support enterprise wide analytics by collaborating with other Grabpay departments to understand business reporting needs and requirements

• Develop analytical framework and performance dashboards on analyst efficiency & productivity, workforce management, chargeback management and performance with report automation and standardization

• Deliver data insights and research findings, leveraging statistical analytics, data visualization and industry knowledge

• Develop financial modeling and analysis for strategic planning and performance tracking

• Collaborate with cross-functional groups such as Engineering, Data Science, Risk and Product Management to improve processes, system functionalities, and fraud detection methods

• Acting as a mentor to help train and upskill junior analyst in data analytics and sql

The must haves:

• Bachelor's degree in Statistics, Analytics, Economics, Mathematics, Engineering or other quantitative subjects are required

• Proficient in RDBMS such as PostgreSQL or MySQL

• Strong experience in Tableau and Excel or other data visualization tools

• Strong analytical experience and business acumen, preferably in payments or e-commerce

• General knowledge of call center data management tools and systems - exposure to Zendesk or similar telephony systems highly desirable.

Nice to haves:

• Good understanding of the payment space preferably with hands-on knowledge of fraud, payments and risk

• Experience using statistical programming languages (R, Python ect) to manipulate data and draw insights from large data sets is a plus